Writing Engineering Abstracts(50)

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    Writing Engineering Abstracts(50)

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    :(+)

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    (1 of 2) (+) Despite the ability of SEM toidentify the grain structure of a solar cell, the area that it scans isrelatively small for the entire solar cell. As constructing I-V curvedata requires time for testing, a wafer must be scanned manytimes using SEM to cover the entire area. However, the

    conventional procedure to identify defective cells in a module islaborious and time consuming. Therefore, this workdescribes an inspection system to identify defects in silicon-based solar cells, in particular unqualified cells, by locating themand calculating the percentage of the defective area immediately.The proposed system consists of near-infrared (NIR) image

    sensing electronic circuits and a data processing controlcomputer in real time.

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    (2 of 2)Solar cell performance is evaluated using the I-V curve. Ifthe I-V curve represents inadequate electrical power behavior,the grain structure is then observed using scanning electronmicroscopy (SEM) to identify the problem. Next, before I-Vtesting for solar cell defects, the proposed inspection system isimplemented to identify the defective area for the entire solar cellrapidly. Additionally, the percentage of the defective area in theentire solar cell module is determined immediately owing to thereal time data processing control computer of the proposedsystem, making it feasible to locate unqualified cells without

    constructing an I-V curve. Analysis resultsindicate that the proposed inspection system locates defectsimmediately and determines the detailed reason for defects inthe grain structure by using SEMS. Importantly, the proposed inspection system for solar cell defects

    is highly efficient in terms of identifying defective areas.

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    (2 of 2) Analysis results indicate that theproposed non-destructive inspection method determinesthe sugar content of fruit with an accuracy exceeding 85%.Importantly, the proposed methoddemonstrates the effect iveness of near infrared

    absorbance spectrum in accurately predicting the sugarcontents of fruit.

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